Analysis of mRNA Dynamics Using RNA Sequencing Data

Methods Mol Biol. 2022;2515:129-150. doi: 10.1007/978-1-0716-2409-8_9.

Abstract

The RNA abundance of each gene is determined by its rates of transcription and RNA decay. Biochemical experiments that measure these rates, including transcription inhibition and metabolic labelling, are challenging to perform and are largely limited to in vitro settings. Most transcriptomic studies have focused on analyzing changes in RNA abundances without attributing those changes to transcriptional or posttranscriptional regulation. Estimating differential transcription and decay rates of RNA molecules would enable the identification of regulatory factors, such as transcription factors, RNA binding proteins, and microRNAs, that govern large-scale shifts in RNA expression. Here, we describe a protocol for estimating differential stability of RNA molecules between conditions using standard RNA-sequencing data, without the need for transcription inhibition or metabolic labeling. We apply this protocol to in vivo RNA-seq data from individuals with Alzheimer's disease and demonstrate how estimates of differential stability can be leveraged to infer the regulatory factors underlying them.

Keywords: Alzheimer’s disease; Posttranscriptional regulation; RNA binding proteins; RNA decay; RNA degradation; RNA stability; RNA-seq; microRNAs.

MeSH terms

  • Humans
  • MicroRNAs* / genetics
  • RNA Stability* / genetics
  • RNA, Messenger / genetics
  • RNA, Messenger / metabolism
  • Sequence Analysis, RNA / methods
  • Transcriptome

Substances

  • MicroRNAs
  • RNA, Messenger